INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2456-4184 | Impact factor: 8.76 | ESTD Year: 2016
Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.76 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI)
The proliferation of smartphones as it becomes more affordable, is giving many a means to express their hateful and offensive ideas unrestrictedly. Social media websites are the main outlet of such expressions which have inadequate systems for hate speech detection especially for less common languages. Hinglish being a pronunciation based pseudo language, offensive message detection is even more difficult. In the paper, possible techniques to counter this problem have been discussed with main focus on different combinations of text vectorization and neural networks. Count and TF-IDF Vectorizers have been crossed with different neural networks trained on a corpus of Hinglish texts acquired from the Twitter API 2.0. LSTM, BiLSTM, RNN based models were trained and tested. The results consist of a comparative study of these neural networks showcasing RNN model to be working with Count Vectorization most efficiently.
"Performance Analysis of Neural Networks for Offensive-Hinglish Detection", International Journal of Novel Research and Development (www.ijnrd.org), ISSN:2456-4184, Vol.8, Issue 4, page no.c56-c60, April-2023, Available :http://www.ijnrd.org/papers/IJNRD2304208.pdf
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2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
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